公开(公告)号：US20240242119A1

公开(公告)日：2024-07-18

申请号：US18404327

申请日：2024-01-04

Applicant: Nokia Solutions and Networks Oy

Inventor： Chaitanya Aggarwal ,  Tejas Subramanya ,  Mehrnoosh Monshizadeh ,  Vikramajeet Khatri ,  Sina Hojjatinia

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: It may be that data collected, and retrieved, for a model training is not sufficient, and hence additional data may be needed. When it is determined that additional data is needed to complement the data retrieved, synthetic data is generated, and training data is obtained by combining the synthetic data with the data retrieved, and the model training is performed. A ratio of the synthetic data to the training data is determined and the ratio is indicated in a response to a request that caused the model to be trained.

公开(公告)号：US20240242081A1

公开(公告)日：2024-07-18

申请号：US18406374

申请日：2024-01-08

Applicant: Nokia Solutions and Networks Oy

Inventor： Mehrnoosh MONSHIZADEH ,  Vikramajeet Khatri ,  Sina Hojjatinia ,  Chaitanya Aggarwal ,  Tejas Subramanya

IPC: G06N3/088 ,  G06N3/045

CPC classification number: G06N3/088 ,  G06N3/045

Abstract: Two competing machine learning based models, a first model for generating synthetic data, and a second model for classifying input data to synthetic data and real data, are trained by training the second model until its accuracy meets a preset rule, and then the first model is trained. After training the first model, training of models is repeated until an end criterium is met.